Welcome

Welcome to my personal website. It is mainly a repository for my papers, but increasingly also for the data and code supporting these papers.
I have a broad interest in human behaviour and in how the brain orchestrates this behaviour. My current research topics range from the decoding of psychological processes from the brain, to investigating brain responses with naturalistic stimuli (movies), to the neural underpinnings of cheating and deception, and to the role of context in decision-making. These research lines are outlined briefly below. Past lines of research include the role of hormones in behaviour and brain processes, the neural substates of emotions, goal-directed motivation and their control, performance monitoring and the impact of fatigue on cognition.
Cheating, unfairness and deception
Dishonest behaviour, such as tax evasion, music piracy or
fraud, is highly prevalent in our society and inflicts huge economic
costs. Every day, we are faced with the conflict between the temptation
to cheat and deceive for financial gains and maintaining a positive
image of ourselves as being a ‘good person’. In
this line of research, we investigate the psychological and neural
underpinnings of decisions to either cheat and deceive, or to remain
fair and honest.
We find that particularly individual differences in the engagement of
cognitive control and theory of mind drive decisions to be fair and
honest (or not). For example, in one study we found that cognitive
control may override an individual’s moral default, allowing
honest people to cheat, whereas it enables cheaters to be honest. These
insights contribute to a deeper understanding of individual differences
in honesty and may aid in developing more targeted interventions aiming
at reducing dishonesty.
Decoding psychological processes from the brain
The human psyche pretty much remains a black box: we can
observe or even manipulate the input a person’s psychological
system receives, but not the feelings or cognitive processes that are
evoked by this input. Likewise, we can observe the decisions made by
the system, but not the feelings or cognitive processes that drove
these decisions. In this line of research, we decode these latent
processes or states from the brain, using machine learning methods
applied to distributed pattern of brain activity.
For example, in two studies (one using EEG, and one using fMRI), we
presented participants with video content while measuring activity from
their brains. Using machine learning, we trained classifiers to
accurately decode the emotional experience evoked by these videos in
our participants. As another example, in every-day life we observe
large differences in honesty and fairness across individuals. In a set
of two studies (using fMRI), we decode idiosyncrasies in the underlying
motivations for honesty and fairness. We find that particularly
individual differences in the engagement of cognitive control and
theory of mind drive differences in prosocial behaviour.
Brains at the movies
In the past, research in neuroscience has used
decontextualized stimuli and highly artificial experimental designs to
study the neural substrate of cognitive processes. Although this
approach has been very successful, as it allows for tightly controlled
experiments and straightforward interpretation of results, it has left
open the question of how the brain responds to events in more
naturalistic settings. In this line of research, we address this issue
by investigating how brain processes unfold during movie watching.
We find that we can track emotions, engagement and preference that
follow the narrative of the presented videos. In addition, we observe
that we can not only predict how well individual participants will like
the movie they are watching, but also how well others will like this
movie. That is, we can predict, from brain activity measured during
movie-watching in a small set of participants, to what extent a
different set of participants will like this movie, and even estimate
how well the movie will do at the box office.